Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study

BACKGROUND: Only around 20–30% of patients with non-small-cell lung cancer (NCSLC) have durable benefit from immune-checkpoint inhibitors. Although tissue-based biomarkers (eg, PD-L1) are limited by suboptimal performance, tissue availability, and tumour heterogeneity, radiographic images might holi...

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Detalles Bibliográficos
Autores principales: Saad, Maliazurina B, Hong, Lingzhi, Aminu, Muhammad, Vokes, Natalie I, Chen, Pingjun, Salehjahromi, Morteza, Qin, Kang, Sujit, Sheeba J, Lu, Xuetao, Young, Elliana, Al-Tashi, Qasem, Qureshi, Rizwan, Wu, Carol C, Carter, Brett W, Lin, Steven H, Lee, Percy P, Gandhi, Saumil, Chang, Joe Y, Li, Ruijiang, Gensheimer, Michael F, Wakelee, Heather A, Neal, Joel W, Lee, Hyun-Sung, Cheng, Chao, Velcheti, Vamsidhar, Lou, Yanyan, Petranovic, Milena, Rinsurongkawong, Waree, Le, Xiuning, Rinsurongkawong, Vadeerat, Spelman, Amy, Elamin, Yasir Y, Negrao, Marcelo V, Skoulidis, Ferdinandos, Gay, Carl M, Cascone, Tina, Antonoff, Mara B, Sepesi, Boris, Lewis, Jeff, Wistuba, Ignacio I, Hazle, John D, Chung, Caroline, Jaffray, David, Gibbons, Don L, Vaporciyan, Ara, Lee, J Jack, Heymach, John V, Zhang, Jianjun, Wu, Jia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10330920/
https://www.ncbi.nlm.nih.gov/pubmed/37268451
http://dx.doi.org/10.1016/S2589-7500(23)00082-1

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